Spots image is the common image information in the field of machine vision and pattern recognition. The character of the spot image is the center of the spot. The spot center is widely used in object tracking in machine vision, high accuracy 3D measurement in vision and celestial navigation.
At present, there are two known methods of locating the center of the spot's image, one is based on the gray value of the pixels, and another is based on the edge. The information of the distribution of the gray value of the spots image is made use by a locating method which is based on the gray value, such as a centroiding algorithm and a curved surface fitting, method etc. The information regarding the shape of the edge is always used by the locating method which is based on the edge, including circle fitting, Hough transform etc.
The method which is based on the gray value has higher accuracy than the method which is based on the edge. Usually, the method of curved surface fitting fits the gray value distribution of the spots image by a 2D Gaussian curved surface, so the method is too complicated. The centroiding algorithm is used most frequently, due to its easy implementation and its high precision. The centroiding algorithm has some improved forms, mainly including the centroiding algorithm with a threshold value and the square weighted centroiding algorithm. The centroiding algorithm with threshold value is to subtract the background threshold from the original image, calculating the centroiding of the pixels which exceeds the threshold value. The square weighted centroiding algorithm uses the square of the gray value to replace the gray value and highlights the influence of the gray value nearer to the center of the spot.
In the prior art, for real-time application in vision dynamic tracking and the requirement of miniaturization in space application, spot centroiding which is to handle a mass of data and the processing exists in parallel, including operation parallelism, image parallelism, neighborhood parallelism, the pixel position parallelism and so on. But at present, the method of the spot centroiding is implemented mostly by the software in the computer. The implementation is done by instruction and is serial, so spot centroiding becomes the bottleneck of the image processing. For real-time spot centroiding, the system of on-chip windowed centroiding is proposed by Jet Propulsion Laboratory (“JPL”), neuro-MOS circuits have been implemented and integrated with a complementary metal oxide semiconductor (“CMOS”) active pixel sensor (“APS”). More than two windows are set to locate spots centroid at the same time by the system. But due to the analog circuit and windowed processing, some disadvantages are as follows:
1) The window can not be set too large otherwise when more than two spots exist in one window, the two spots will be calculated as one spot which will skew the result with this error. Thus, the approximate position and the range must be known ahead to set the window.
2) Because of the limitation of the process and transmission speed, the number of windows can not be too much, so some spot's centroid can not be calculated
3) Because of implementation with the analog circuit, the centroiding algorithm is sensitive to noise which is the source of the error thereof.